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A maintenance driven scheduling cockpit for integrated production and maintenance operation schedule

作     者:Mario Arena Valentina Di Pasquale Raffaele lannone Salvatore Miranda Stefano Riemma 

作者机构:Department of Industrial EngineeringUniversity of SalernoFiscianoSAItaly 

出 版 物:《Advances in Manufacturing》 (先进制造进展(英文版))

年 卷 期:2022年第10卷第2期

页      面:205-219页

核心收录:

学科分类:0202[经济学-应用经济学] 02[经济学] 1201[管理学-管理科学与工程(可授管理学、工学学位)] 020205[经济学-产业经济学] 0809[工学-电子科学与技术(可授工学、理学学位)] 0812[工学-计算机科学与技术(可授工学、理学学位)] 

主  题:Industry 4.0-Maintenance task Production schedule Predictive maintenance Integrated plan 

摘      要:The production and maintenance functions have objectives that are often in contrast and it is essential for management to ensure that their activities are carried out synergistically,to ensure the maximum efficiency of the production plant as well as the minimization of management *** current evolution of ICT technologies and maintenance strategies in the industrial field is making possible a greater integration between production and *** work addresses this challenge by combining theknowledge of the data collected from physical assets for predictive maintenance management with the possibility of dynamic simulate the future behaviour of the manufacturing system through a digital twin for optimal management of maintenance *** paper,indeed,presents a supporting digital cockpit for production and maintenance integrated *** proposes an innovative approach to manage health data from machines being in any production system and provides support to compare the information about their remaining useful life(RUL)with the respective production *** maintenancedriven schedulingcockpit(MDSC)offers,indeed,a supporting decision tool for the maintenance strategy to be implemented that can help production and maintenance managers in the optimal scheduling of preventive maintenance interventions based on RUL *** simulation is performed by varying the production schedule with the maintenance tasks involvement;opportune decisions are taken evaluating the total costs related to the simulated strategy and the impact on the production schedule.

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